Date of Award:

5-2015

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Civil and Environmental Engineering

Committee Chair(s)

Mac McKee

Committee

Mac McKee

Committee

Douglas Ramsey

Committee

David Stevens

Committee

Todd Moon

Committee

David Rosenberg

Abstract

The goals of preserving scarce water resources, cultivating more lands, and saving on irrigation water bills have directed the attention of water resources managers toward the concepts of precision agriculture and, in particular, to precision irrigation. The purpose of precision irrigation is to increase irrigation efficiency to avoid crop water stress, avoid yield reduction due to under-irrigation and leaching of nutrients, runoff, and reduce soil erosion due to over-irrigation. In this study, irrigation efficiency has been defined in terms of irrigation uniformity and the response of the crop to irrigation. Crop water demand, soil moisture, evapotranspiration rate, and potential water losses to deep percolation and runoff have been calculated by using remotely sensed data, field measurements, and learning machines. Sub-field level irrigation water allocation and scheduling have been examined for an agricultural field in Utah. These calculations have been carried out at 30 m by 30 m resolution, which is commensurate with the applied remotely sensed data (Landsat imagery). In addition to a focus on the use of satellite data for irrigation scheduling, this study has developed a similar irrigation water allocation model at a much finer resolution (15 cm by 15 cm) using a different set of remotely sensed data (acquired through use of an autonomous, unmanned remote sensing aircraft called AggieAirTM) to create surface and root zone soil moisture maps at 15 cm resolution. The high-resolution information provides the capability to represent spatial variations within the agricultural field at a compatible resolution with farming management activities. Instead of farmers visually perceiving agricultural field conditions, specifically soil moisture, this study provides a means whereby farmers might gain information about actual soil moisture distribution over the field, which could help in scheduling irrigation and enabling greater precision in the application of irrigation water by identifying dry/wet spots.

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